1. Content Based Image Retrieval (CBIR) of Dermatological Images H.H.W.J Bosman, N. Petkov, M.F. Jonkman

2. Image retrieval: http://images.google.nl

4. CBIR - what is it? Search for images that are similar to an input image Features that might indicate similarity  Color  Texture  Shape  Text tags  etc...

5. iMedia Project – select query http://www-rocq.inria.fr/cgi-bin/imedia/circario.cgi/v2std

6. iMedia Project – query results http://www-rocq.inria.fr/cgi-bin/imedia/circario.cgi/v2std

7. GIFT – select query http://viper.unige.ch/demo/php/demo.php

8. GIFT – query result http://viper.unige.ch/demo/php/demo.php

9. Leiden 19 th -Century Portrait Database http://nies.liacs.nl:1860/cgi-bin/FindImage.pl

10. Leiden 19 th -Century Portrait Database http://nies.liacs.nl:1860/cgi-bin/FindImage.pl

11. CBIR in medical settings Seeking pathologically similar mammogram images Dept of Computer Science at Warwick university http://www2.warwick.ac.uk/fac/sci/dcs/research/mimic/projects/lisprojectpag e

12. CBIR in medical settings http://cobweb.ecn.purdue.edu/~cbirdev/WEB_ASSERT/assert.htm l

13. CBIR in dermatology

15. Methods - the dataset 211 dermatological images from the UMCG image database Divided into 4 classes: Red, White, Blue, Brown Manually selecting area of healthy skin (70,110,90) and lesion skin (120,95,80)‏

16. CBIR in dermatology

19. Results with only color features 75% correct retrieval White is retrieved best Blue is the most difficult to retrieve Results vary with the ‘goodness’ of the selection of different regions.

20. From CBIR to CBCR (content based case retrieval)‏ TEST CASE defined by PROVOKE query: Plaats:...Efflorescentie:... Rangschikking:... Omvang:... Kleur/Vorm/Omtrek:

21. Questions or suggestions?